Results 41 to 50 of about 10,729 (237)
Frontiers in Psychology, 2022 While we cannot directly measure the psychological preferences of individuals, and the moral, emotional, and cognitive tendencies of people from the past, we can use cultural artifacts as a window to the zeitgeist of societies in particular historical ...
Mauricio de Jesus Dias Martins +1 more
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Word embedding for social sciences: an interdisciplinary survey [PDF]
PeerJ Computer ScienceMachine learning models learn low-dimensional representations from complex high-dimensional data. Not only computer science but also social science has benefited from the advancement of these powerful tools.
Akira Matsui, Emilio Ferrara
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Pengaruh Parameter Word2Vec terhadap Performa Deep Learning pada Klasifikasi Sentimen [PDF]
, 2021 The difficulty of sentiment classification on this big data can be overcome using deep learning. Before the deep learning training and testing process is carried out, a word features extraction process is needed. Word2Vec as a word features extraction is
Handayani, S. F. (Sharfina) +11 more
core +1 more source
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2018 The problem of word sense disambiguation (WSD) is considered in the article. Set of synonyms (synsets) and sentences with these synonyms are taken. It is necessary to automatically select the meaning of the word in the sentence.
Andrew Krizhanovsky +2 more
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Techno.Com, 2023 Tranportasi merupakan hal yang penting bagi masyarakat dalam mobilitas sehari-hari. Karena memiliki peranan penting dan dapat memudahkan kehidupan masyarakat, pemerintah mulai mengoptimalkan pembangunan sarana transportasi dan memulai inovasi digital ...
Mega Vebika Shyahrin +2 more
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Connection Science, 2022 The word embedding model word2vec tends to ignore the importance of a single word to the entire document, which affects the accuracy of the news text classification method.
Weidong Zhao +4 more
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Opening the Black Box: Finding Osgood’s Semantic Factors in Word2vec Space
Информатика и автоматизация, 2022 State-of-the-art models of artificial intelligence are developed in the black-box paradigm, in which sensitive information is limited to input-output interfaces, while internal representations are not interpretable.
Ilya Surov
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Using Word2Vec Recommendation for Improved Purchase Prediction [PDF]
2020 International Joint Conference on Neural Networks (IJCNN), 2020 Purchase prediction can help e-commerce planners plan their stock and personalised offers. Word2Vec is a well-known method to explore word relations in sentences for sentiment analysing by creating vector representation of words. Word2Vec models are used in many works for product recommendations.
Ramazan Esmeli +2 more
openaire +3 more sources
The Word2vec models: CBOW and Skip-gram.
, 2022 The Word2vec models: CBOW and Skip-gram.
Naglaa Fathy Hassan (13189914) +2 more
core +1 more source
Advanced Materials, EarlyView.Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source